Can “smarter” cities trump the “feral” trend?

“By overcoming silos in the way we think, we are able to better visualize how our city systems work together and develop policies that achieve multiple objectives to help realize the full potential of our city.” –Sam Adams, mayor of Portland, OR, commenting on the use of a new interactive computer model developed by IBM to shape his city’s planning policies

Last week’s post about the potential growth of so-called “feral cities” in the not-so-distant future generated a few interesting responses – in no small part due to the sudden outbreak of violent riots in London, providing an extremely vivid example of what “feral city” forecasters are worried about.

Transportation’s ability to serve the needs of such large and perhaps at times unstable enclaves of humanity, both in terms of moving people and freight, is but one reason for why truckers should be concerned if this so-called trend towed “feral-ism” gains traction.

Yet it’s not as though city planners are throwing up their hands in terms of more effectively shaping the structure of future cities. Indeed, one year-long research effort by IBM and the city of Portland, OR, seeks to use technology to allow planners to more effectively manage future urban growth.

“All cities are made up of a complex system of systems that are inextricably linked,” noted Michael Littlejohn, vp-strategy for the Smarter Cities program at IBM. “The city of Portland has served as a living laboratory during our year-long collaboration to explore how complex city systems behave over time.”

He added that while other analytical approaches rely on breaking a problem down into smaller and smaller pieces, the model IBM created recognizes that the behavior of a system as a whole can be different from what might be anticipated by looking at its parts.

“Using this model, the City of Portland can experiment with different scenarios to see how their decisions might affect various parts of the city over the next 25 years,” Littlejohn pointed out.

In short, IBM's System Dynamics for Smarter Citiesmodel is designed to help mayors and other municipal officials reduce the unintended negative consequences of municipal actions on citizens, as well as uncover hidden beneficial relationships among municipal policies.

It also seeks to better connect what Littlejohn dubs the “relationships among the city's core systems” into one program so officials can view how particular policies affect a city’s economy, housing, education, public safety, transportation, healthcare/wellness, government services and utilities.

[For example, take the transportation issues endemic in large cities like Mexico City, where the population exceeds 20 million.]

He noted that IBM approached the city of Portland in late 2009 about developing this type of “holistic” computer model, then began work on it in April 2010 via series of sessions with over 75 Portland-area subject matter experts to learn about specific “system interconnection” points within Portland.

Later, with help from researchers at Portland State University and software company Forio Business Simulations, IBM and Portland’s city administration collected approximately 10 years of historical data, on which it based this computer model to provide Portland’s Bureau of Planning and Sustainability with what IBM called “n interactive visual model” that allows them to navigate and test changes in the city's systems.

So, how does something like this work? Take for example the city’s stated policy goal of reducing carbon emissions by 40% by 2030, followed by an 80% reduction by 2050.

The city already figured that shifting some trips away from driving to active forms of transportation, such as walking and biking, would be a part of how it would meet such “carbon reduction” goals.

However, the IBM model went further to discern that, on average, obesity levels would decline as more people walk and bike. Similarly, if obesity levels go down, active transportation becomes a more attractive option to more people. Since shifting to walking and biking reduces driving trips, the obesity/active transport loop could be a self-reinforcing policy lever to address carbon goals, IBM’s model indicates.

OK, now, sure: I can see truckers rolling their eyes already on this one, perhaps envisioning this “finding” as a way for city planners to justify redirecting precious fuel tax revenues towards no-highway expenditures, such as a building bicycle and walking paths.

Fair enough. But perhaps that same data set shows that restricting carbon emissions might limit the number of trucks that can operate within the city on a daily basis – restricting the ability of grocers, merchants and others to receive the stream of foodstuffs and goods city residents rely on to survive.

Or maybe this computer model could show ways to improve the distribution of freight hauled by trucks, so fewer are required – better matching the flow of freight with available trucking capacity.

We’ll only really know once we start viewing the transportation needs of our ever-expanding urban centers though “holistic” lenses like the “Smarter Cities” effort.